Only set save_tree_error when training the final model

pipeline/01-train.R

@@ -145,7 +145,9 @@ lgbm_model <- parsnip::boost_tree(
  # using floor(log2(num_leaves)) + add_to_linked_depth. Useful since
  # otherwise Bayesian opt spends time exploring irrelevant parameter space
  link_max_depth = params$model$parameter$link_max_depth,
- save_tree_error = comp_enable,
+ # Always initialize save_tree_error to false until we're ready to train
+ # the final model, since it's incompatible with CV
+ save_tree_error = FALSE,
 
  ### 4.1.2. Tuned Parameters ------------------------------------------------
 
@@ -346,12 +348,14 @@ if (cv_enable) {
 
 # Finalize the model specification by disabling early stopping, instead using
 # the maximum number of iterations used during the best cross-validation round
-# OR the default `num_iterations` if CV was not performed
+# OR the default `num_iterations` if CV was not performed. Also enable comps
+# if they're configured to run, since they're incompatible with CV
 lgbm_model_final <- lgbm_model %>%
  set_args(
  stop_iter = NULL,
  validation = 0,
- trees = lgbm_final_params$num_iterations
+ trees = lgbm_final_params$num_iterations,
+ save_tree_errors = comp_enable
  )
 
 # Fit the final model using the training data and our final hyperparameters